System, vehicle and method for adapting a driving condition of a vehicle upon detecting an event in an environment of the vehicle

ABSTRACT

Methods and systems are provided for adapting a driving condition of a vehicle. The system includes a non-transitory computer readable medium having stored thereon a pre-programmed driving maneuver of the vehicle. The system also includes a processor configured to obtain audio data of acoustic sources in the environment of the vehicle. The processor is further configured to determine a receiving direction of the acoustic source based on the audio data. The processor is further configured to determine whether the acoustic source are located within the maneuver of the vehicle based on the pre-programmed or updated driving maneuvers and the determined receiving direction of the acoustic source. Furthermore, the processor is configured to determine a range between the vehicle and the acoustic source in order to determine that the acoustic source is located within the driving path of the vehicle.

INTRODUCTION

The technical field generally relates to control systems for controllingpartially or fully autonomous vehicles, and more particularly relates toa system, a vehicle and a method for adapting a driving condition of avehicle upon detecting an event in an environment of the vehicle.

A driving scenario of a vehicle often includes many different situationsin which the driver must interact, for example, to avoid a collisionbetween the vehicle and an object surrounding the vehicle. Such adriving scenario may involve the vehicle driving straight forward,making a left or right turn or a complex parking maneuver where thevehicle subsequently changes between driving forwards and backwards.These driving maneuvers can be carried out by the vehicle partially orfully autonomously, in particular using a processor of the vehiclesystem configured to drive such maneuvers. However, complex andunexpected driving scenarios or events can occur which makes itdifficult for the autonomous vehicle system to predict possible changesof such a driving scenario or to determine whether an intervention ofthe vehicle system is required to avoid dangerous situations, forexample to avoid a collision of the vehicle and an object nearby.

Accordingly, it is desirable to take into account and evaluate acousticsources in the environment of a vehicle when controlling the vehicle inorder to increase safety for the passengers and surrounding persons orobjects. In addition, it is desirable to improve the redundancy ofsensors for detecting environmental parameters used to control avehicle. Furthermore, other desirable features and characteristics ofthe present invention will become apparent from the subsequent detaileddescription and the appended claims, taken in conjunction with theaccompanying drawings and the foregoing technical field and background.

SUMMARY

A system is provided for adapting a driving condition of a vehicle upondetecting an event in an environment of the vehicle. The system includesa non-transitory computer readable medium having stored thereon apre-programmed driving maneuver of the vehicle, wherein thepre-programmed driving maneuver is indicative of a driving path of thevehicle. The system also includes a processor configured to obtain audiodata of an acoustic source in the environment of the vehicle. Theprocessor is further configured to determine a receiving direction ofthe acoustic source based on the audio data, the receiving directionbeing indicative of a direction of the acoustic source relative to thevehicle. The processor is further configured to determine whether theacoustic source is located within the driving path of the vehicle basedon the pre-programmed driving maneuver and the determined receivingdirection of the acoustic source. Furthermore, the processor isconfigured to determine a range between the vehicle and the acousticsource if it is determined that the acoustic source is located withinthe driving path of the vehicle. The processor is configured to controlthe vehicle based on the determined range, for example by changing thevelocity of the vehicle or a driving direction of the vehicle. Thecontrolling of the vehicle based on the determined range may includefurther processing steps of the determined range before a control of thevehicle is initiated. The processor may further be configured tore-program the driving maneuver and/or to stop the vehicle. Thus, anupdated driving maneuver can be generated which is indicative of theupcoming driving path of the vehicle. The update of the driving path canbe carried out in real time.

In one embodiment, the processor is further configured to determine therange between the vehicle and the acoustic source only if it isdetermined that the acoustic source is located within the driving pathof the vehicle.

In one embodiment, the non-transitory computer readable medium stores aset of audio models, each of the audio models being indicative of arespective acoustic scenario, wherein the processor is furtherconfigured to determine a type of the acoustic source based on theobtained audio data between the acoustic source and the set of audiomodels.

In one embodiment, the non-transitory computer readable medium furtherstores a set of audio models, each of the audio models being indicativeof a respective acoustic scenario, wherein the processor is furtherconfigured to determine an urgency estimation of a current drivingscenario based on the obtained audio data of the acoustic source and theset of audio models, wherein a positive urgency estimation is indicativeof an upcoming collision event of the acoustic source and the vehicle.

In one embodiment, the processor is further configured to obtain secondaudio data of the acoustic source if the result of the urgencyestimation is indeterminable, and to subsequently determine a secondurgency estimation of another driving scenario based on the obtainedsecond audio data of the acoustic source and the set of audio models.

In one embodiment, the processor is further configured to obtain furthersensor data of the acoustic source in the environment of the vehicle,and to provide fused data based on a fusion of the further sensor dataof the acoustic source with the audio data of the acoustic source.

In one embodiment, the further sensor data is obtained from a camera, aLidar and/or a radar.

In one embodiment, the processor is further configured to verify theurgency estimation of the current driving scenario based on the fuseddata.

In one embodiment, the processor is further configured to control thevehicle based on the verified urgency estimation of the current drivingscenario, wherein controlling the vehicle by the processor includeschanging the driving path of the vehicle or stopping the vehicle.

In one embodiment, the acoustic source is a person, another vehicle, ananimal and/or a loudspeaker. However, it is noted that any otheracoustic source emitting an acoustic noise, tone or signal may beconsidered as an acoustic source.

In one embodiment, the system further includes an audio sensorarrangement having a plurality of audio sensor arrays, wherein each ofthe plurality of audio sensor arrays in the audio sensor arrangement islocated at a distinct location of the vehicle.

In one embodiment, the audio sensor arrangement comprises two audiosensor arrays, each of the two audio sensor arrays having two audiosensors, for example microphones.

In one embodiment, the processor is further configured to determine therange between the vehicle and the acoustic source based on triangulationusing the two audio sensor arrays.

In one embodiment, the processor is further configured to obtain audiodata of a plurality of acoustic sources in the environment of thevehicle, to determine a receiving direction for each of the acousticsources based on the audio data, the receiving directions beingindicative of respective directions of the acoustic sources relative tothe vehicle, and to determine for each of the acoustic sources whetherthe acoustic source is located within the driving path of the vehiclebased on the pre-programmed driving maneuver and the determinedreceiving directions of each of the acoustic sources. It is possiblethat, for each acoustic source, two or more receiving directions may bedetermined using two or more audio sensor arrays, wherein the at leasttwo receiving directions can then be used to localize the acousticsource.

In one embodiment, the processor is further configured to select theacoustic sources that are determined to be located within the drivingpath of the vehicle, and to determine a range between the vehicle andeach of the selected acoustic sources, and to discard the acousticsources that are determined not to be located within the driving path ofthe vehicle.

In one embodiment, the processor is further configured to determine aminimum range out of the determined ranges between the selected acousticsources and the vehicle, and to select a single acoustic source from theplurality of acoustic sources, which is most proximal to the vehicle.

In one embodiment, the system further includes an audio sensorarrangement having a plurality of audio sensor arrays, wherein theprocessor is further configured to select one audio sensor arrayreceiving a maximum signal-to-noise-ratio from the selected singleacoustic source being most proximal to the vehicle, and to select anaudio channel for an audio signal from an audio sensor of the selectedaudio sensor array.

In one embodiment, the processor is further configured to determine anurgency estimation of a current driving scenario based on the audiosignal and a set of audio models stored on the non-transitory computerreadable medium.

A vehicle is provided for adapting a driving condition upon detecting anevent in an environment of the vehicle. The vehicle includes anon-transitory computer readable medium having stored thereon apre-programmed driving maneuver of the vehicle, wherein thepre-programmed driving maneuver is indicative of a driving path of thevehicle. The vehicle further includes a processor configured to obtainaudio data of an acoustic source in the environment of the vehicle, todetermine a receiving direction of the acoustic source based on theaudio data, the receiving direction being indicative of a direction ofthe acoustic source relative to the vehicle, to determine whether theacoustic source is located within the driving path of the vehicle basedon the pre-programmed driving maneuver and the determined receivingdirection of the acoustic source, and to determine a range between thevehicle and the acoustic source if it is determined that the acousticsource is located within the driving path of the vehicle. The processoris further configured to control the vehicle based on the determinedrange. The determination of the receiving direction of the acousticsource and the determination whether the acoustic source is locatedwithin the driving path of the vehicle as well as the determination ofthe range between the vehicle and the acoustic source can be appliedusing an updated maneuver, in addition or instead, to using thepre-programmed maneuver.

A method is provided for adapting a driving condition of a vehicle upondetecting an event in an environment of the vehicle. The method includesthe step of storing, on a non-transitory computer readable medium, apre-programmed driving maneuver of the vehicle, wherein thepre-programmed driving maneuver is indicative of a driving path of thevehicle. The method further includes the step of obtaining, by aprocessor, audio data of an acoustic source in the environment of thevehicle. The method further includes the step of determining, by theprocessor, a receiving direction of the acoustic source based on theaudio data, the receiving direction being indicative of a direction ofthe acoustic source relative to the vehicle. The method further includesthe step of determining, by the processor, whether the acoustic sourceis located within the driving path of the vehicle based on thepre-programmed driving maneuver and the determined receiving directionof the acoustic source. The method further includes the step ofdetermining, by the processor, a range between the vehicle and theacoustic source if it is determined that the acoustic source is locatedwithin the driving path of the vehicle. The method further includes thestep of controlling the vehicle based on the determined range.

BRIEF DESCRIPTION OF THE DRAWINGS

The exemplary embodiments will hereinafter be described in conjunctionwith the following drawing figures, wherein like numerals denote likeelements, and wherein:

FIG. 1 is a vehicle having a system for adapting a driving condition ofthe vehicle upon detecting an event in an environment of the vehicle inaccordance with an embodiment;

FIG. 2 is a schematic diagram showing a system architecture of thesystem for adapting a driving condition of a vehicle upon detecting anevent in an environment of the vehicle in accordance with an embodiment;

FIGS. 3A and 3B show a block diagram of a method for adapting a drivingcondition of a vehicle upon detecting an event in an environment of thevehicle in accordance with an embodiment;

FIG. 4 is a driving scenario of the vehicle of FIG. 1 in accordance withan embodiment;

FIG. 5 is a driving scenario of the vehicle of FIG. 1 in accordance withanother embodiment;

FIG. 6 is an audio sensor arrangement of a vehicle of FIG. 1 having asingle audio sensor array in accordance with another embodiment;

FIG. 7 is an audio sensor arrangement of the vehicle of FIG. 1 havingtwo rear audio sensor arrays in accordance with an embodiment;

FIG. 8 is an audio sensor arrangement of the vehicle of FIG. 1 havingtwo centrally arranged audio sensor arrays in accordance with anembodiment;

FIG. 9 is an audio sensor arrangement of the vehicle of FIG. 1 havingtwo front audio sensor arrays in accordance with an embodiment; and

FIG. 10 is an audio sensor arrangement of the vehicle of FIG. 1 havingfour audio sensor arrays in accordance with an embodiment.

DETAILED DESCRIPTION

The following detailed description is merely exemplary in nature and isnot intended to limit the application and uses. Furthermore, there is nointention to be bound by any expressed or implied theory presented inthe preceding technical field, background, brief summary or thefollowing detailed description. As used herein, the term module refersto any hardware, software, firmware, electronic control component,processing logic, and/or processor device, individually or in anycombination, including without limitation: application specificintegrated circuit (ASIC), an electronic circuit, a processor (shared,dedicated, or group) and memory that executes one or more software orfirmware programs, a combinational logic circuit, and/or other suitablecomponents that provide the described functionality.

Embodiments of the present disclosure may be described herein in termsof functional and/or logical block components and various processingsteps. It should be appreciated that such block components may berealized by any number of hardware, software, and/or firmware componentsconfigured to perform the specified functions. For example, anembodiment of the present disclosure may employ various integratedcircuit components, e.g., memory elements, digital signal processingelements, logic elements, look-up tables, or the like, which may carryout a variety of functions under the control of one or moremicroprocessors or other control devices. In addition, those skilled inthe art will appreciate that embodiments of the present disclosure maybe practiced in conjunction with any number of systems, and that thesystems described herein is merely exemplary embodiments of the presentdisclosure.

For the sake of brevity, conventional techniques related to signalprocessing, data transmission, signaling, control, and other functionalaspects of the systems (and the individual operating components of thesystems) may not be described in detail herein. Furthermore, theconnecting lines shown in the various figures contained herein areintended to represent example functional relationships and/or physicalcouplings between the various elements. It should be noted that manyalternative or additional functional relationships or physicalconnections may be present in an embodiment of the present disclosure.

With reference to FIG. 1, a vehicle 10 is shown in accordance withvarious embodiments. The vehicle 10 generally includes a chassis 12, abody 14, front wheels 16, and rear wheels 18. The body 14 is arranged onthe chassis 12 and substantially encloses components of the vehicle 10.The body 14 and the chassis 12 may jointly form a frame. The wheels 16and 18 are each rotationally coupled to the chassis 12 near a respectivecorner of the body 14.

In various embodiments, the vehicle 10 is an autonomous vehicle. Theautonomous vehicle 10 is, for example, a vehicle that is automaticallycontrolled to carry passengers from one location to another. The vehicle10 is depicted in the illustrated embodiment as a passenger car, but itshould be appreciated that any other vehicle including motorcycles,trucks, sport utility vehicles (SUVs), recreational vehicles (RVs),marine vessels, aircraft, etc., can also be used. In an exemplaryembodiment, the autonomous vehicle 10 is a so-called Level Four or LevelFive automation system. A Level Four system indicates “high automation”,referring to the driving mode-specific performance by an automateddriving system of all aspects of the dynamic driving task, even if ahuman driver does not respond appropriately to a request to intervene. ALevel Five system indicates “full automation”, referring to thefull-time performance by an automated driving system of all aspects ofthe dynamic driving task under all roadway and environmental conditionsthat can be managed by a human driver. It is appreciated, however, thatthe autonomous vehicle 10 may have any automation level from a Level Twosystem to a Level Five system.

As shown, the autonomous vehicle 10 generally includes a propulsionsystem 20, a transmission system 22, a steering system 24, a brakesystem 26, a sensor system 28, an actuator system 30, at least one datastorage device 32, at least one controller 34, and a communicationsystem 36. The propulsion system 20 may, in various embodiments, includean internal combustion engine, an electric machine such as a tractionmotor, and/or a fuel cell propulsion system. The transmission system 22is configured to transmit power from the propulsion system 20 to thevehicle wheels 16 an 18 according to selectable speed ratios. Accordingto various embodiments, the transmission system 22 may include astep-ratio automatic transmission, a continuously-variable transmission,or other appropriate transmission. The brake system 26 is configured toprovide braking torque to the vehicle wheels 16 and 18. The brake system26 may, in various embodiments, include friction brakes, brake by wire,a regenerative braking system such as an electric machine, and/or otherappropriate braking systems. The steering system 24 influences aposition of the of the vehicle wheels 16 and 18. While depicted asincluding a steering wheel for illustrative purposes, in someembodiments contemplated within the scope of the present disclosure, thesteering system 24 may not include a steering wheel.

The sensor system 28 includes one or more sensing devices 40 a-40 n thatsense observable conditions of the exterior environment and/or theinterior environment of the autonomous vehicle 10. The sensing devices40 a-40 n can include, but are not limited to, radars, Lidars (lightdetection and ranging), acoustic sensors, global positioning systems,optical cameras, thermal cameras, ultrasonic sensors, and/or othersensors. For example, the sensing devices include an acoustic sensorlike a microphone, etc. The actuator system 30 includes one or moreactuator devices 42 a-42 n that control one or more vehicle featuressuch as, but not limited to, the propulsion system 20, the transmissionsystem 22, the steering system 24, and the brake system 26. In variousembodiments, the vehicle features can further include interior and/orexterior vehicle features such as, but are not limited to, doors, atrunk, and cabin features such as air, music, lighting, etc. (notnumbered).

The communication system 36 is configured to wirelessly communicateinformation to and from other entities 48, such as but not limited to,other vehicles (“V2V” communication,) infrastructure (“V2I”communication), remote systems, and/or personal devices. In an exemplaryembodiment, the communication system 36 is a wireless communicationsystem configured to communicate via a wireless local area network(WLAN) using IEEE 802.11 standards or by using cellular datacommunication. However, additional or alternate communication methods,such as a dedicated short-range communications (DSRC) channel, are alsoconsidered within the scope of the present disclosure. DSRC channelsrefer to one-way or two-way short-range to medium-range wirelesscommunication channels specifically designed for automotive use and acorresponding set of protocols and standards.

The data storage device 32 stores data for use in automaticallycontrolling the autonomous vehicle 10. In various embodiments, the datastorage device 32 stores defined maps of the navigable environment. Invarious embodiments, the defined maps may be predefined by and obtainedfrom a remote system. For example, the defined maps may be assembled bythe remote system and communicated to the autonomous vehicle 10(wirelessly and/or in a wired manner) and stored in the data storagedevice 32. As can be appreciated, the data storage device 32 may be partof the controller 34, separate from the controller 34, or part of thecontroller 34 and part of a separate system.

The controller 34 includes at least one processor 44 and a computerreadable storage device or media 46. The computer readable storage media46 and/or the storage device 32 may store a pre-programmed drivingmaneuver of the vehicle 10, wherein the pre-programmed driving maneuvermay be indicative of an upcoming driving path of the vehicle 10. Theprocessor 44 can be any custom made or commercially available processor,a central processing unit (CPU), a graphics processing unit (GPU), anauxiliary processor among several processors associated with thecontroller 34, a semiconductor based microprocessor (in the form of amicrochip or chip set), a macroprocessor, any combination thereof, orgenerally any device for executing instructions. The computer readablestorage device or media 46 may include volatile and nonvolatile storagein read-only memory (ROM), random-access memory (RAM), and keep-alivememory (KAM), for example. KAM is a persistent or non-volatile memorythat may be used to store various operating variables while theprocessor 44 is powered down. The computer-readable storage device ormedia 46 may be implemented using any of a number of known memorydevices such as PROMs (programmable read-only memory), EPROMs(electrically PROM), EEPROMs (electrically erasable PROM), flash memory,or any other electric, magnetic, optical, or combination memory devicescapable of storing data, some of which represent executableinstructions, used by the controller 34 in controlling the autonomousvehicle 10.

The instructions may include one or more separate programs, each ofwhich comprises an ordered listing of executable instructions forimplementing logical functions. The instructions, when executed by theprocessor 44, receive and process signals from the sensor system 28,perform logic, calculations, methods and/or algorithms for automaticallycontrolling the components of the autonomous vehicle 10, and generatecontrol signals to the actuator system 30 to automatically control thecomponents of the autonomous vehicle 10 based on the logic,calculations, methods, and/or algorithms. Although only one controller34 is shown in FIG. 1, embodiments of the autonomous vehicle 10 caninclude any number of controllers 34 that communicate over any suitablecommunication medium or a combination of communication mediums and thatcooperate to process the sensor signals, perform logic, calculations,methods, and/or algorithms, and generate control signals toautomatically control features of the autonomous vehicle 10.

In various embodiments, one or more instructions of the controller 34are embodied. The controller includes the non-transitory computerreadable medium 46 that stores a pre-programmed driving maneuver of thevehicle 10, which is indicative of a driving path of the vehicle 10 and,in particular indicates a driving path along which the vehicle 10 willtravel. The controller also includes the processor 44 which isconfigured to obtain audio data of at least one acoustic source 41 inthe environment of the vehicle 10. The acoustic source 41 may be anysource emitting an acoustic wave or sound wave travelling, for example,through the air from the acoustic source 41 to the vehicle 10. Thecontroller 34, in particular the functionality of the processor 44 willbe described in more detail with reference to FIG. 2.

FIG. 2 is a schematic diagram showing the system architecture of thesystem 1 for adapting a driving condition of the vehicle 10 shown inFIG. 1. The system 1 may be integrated in the vehicle 10, wherein thevehicle 10 is an autonomous vehicle (AV). The vehicle 10 comprises anaudio sensor arrangement 40 including audio sensor arrays 40 a-40 d forsensing an acoustic signal 41 a, for example a sound wave or acousticwave, from an acoustic source 41 in the environment of the vehicle 10.Each of the acoustic sensor arrays 40 a-40 d is arranged at a distinctlocation at, on or within the vehicle 10. Each of the audio sensorarrays 40 a-40 d may include one or more audio sensors, for examplemicrophones. In the example shown in FIG. 2, the acoustic source 41 is aperson shouting or producing a noise in the environment. The audiosensor arrays 40 a-40 d receive the acoustic signal 41 a from the personand generate acoustic signal data 41 b which are provided to theprocessor 44. It is noted that the processor 44 as well as the AVvehicle controller or maneuver system module 30 are depicted separate tothe vehicle 10 for reasons of clarity, however it is to be understoodthat the processor 44 and also the AV controller or maneuver systemmodule 30 of an exemplary embodiment, are parts of the vehicle 10 orintegrated into the vehicle 10. Different sensor array arrangements willbe described with reference to FIGS. 6 to 10.

In an exemplary embodiment, the processor 44 comprises an arrayprocessing module 44 a configured to obtain audio data of the acousticsource 41 based on the acoustic signal data 41 b from the audio sensorarrays 40 a-40 d. Based on these audio data, the processor 44 determinesa receiving direction of the acoustic source 41, wherein the receivingdirection is indicative of a direction of the at least one acousticsource 41 relative to the vehicle 10. The receiving direction may, forexample, be measured with reference to a longitudinal axis of thevehicle 10. The receiving direction therefore indicates the location ofthe acoustic source 41 relative to the vehicle 10, for example usingthree-dimensional coordinates. In particular, two receiving directionsmay indicate the location of the acoustic source 41. Therefore, at leasttwo audio sensor arrays 40 a-40 d may be used to determine receivingdirections of the acoustic source 41 for each of the at least two audiosensors arrays 40 a-40 d in order to determine the location of theacoustic source 41. Three-dimensional coordinates may be used todetermine the location of the acoustic source 41, wherein it may bepossible to ignore acoustic sources 41 that are located above the road,wherein acoustic sources 41 that lie on the road may be furtherconsidered. In an exemplary embodiment, all audio sensor arrays 40 a-40d are used to determine, i.e. localize the acoustic source 41. Thismeans that each audio sensor array 40 a-40 d determines one receivingdirection for the acoustic source 41 so that, for each audio sensorarray 40 a-40 d, one respective receiving direction of the acousticsource 41 is obtained. These receiving directions are then used tolocalize the acoustic source 41 and to estimate whether it is located inthe driving path or not, i.e. to estimate whether it can be excludedthat the acoustic source is located within the driving path or not. Thelocalization is carried out by the localization module 44 b of theprocessor 44. The localization may also use information from aninter-array energy difference which is calculated based on the intensityof the audio signals 41 a received by each of the audio sensor arrays 40a-40 d. In this manner, a receiving direction of the acoustic source 41relative to the vehicle 10 can be determined and therefore the acousticsource 41 may be localized such that a location of the acoustic source41 relative to the vehicle 10 can be determined, for example usingthree-dimensional coordinates. However, it might be preferred that thelocalization is determined based on two receiving directions. Energydifferences may additionally be used to eliminate hypotheticaldirections. The described process may be referred to as a low latency,short-range maneuver dependent localization of acoustic sources 41.

In an exemplary embodiment, the localization of the acoustic sources 41can be carried out based on an inter-array energy level differenceelimination by the localization module 44 b of processor 44. Thisinter-array energy level difference elimination may include alocalization based on an acoustic intensity or energy determination ofthe considered acoustic sources 41, i.e. finding the acoustic source 41from which the strongest acoustic signal 41 a is received by thedifferent audio sensor arrays 40 a-40 d.

In an exemplary embodiment, the processor 44 estimates whether theacoustic source 41 lies within the driving path (not shown) of thevehicle 10 based on the pre-programmed driving maneuver or an updateddriving maneuver and the determined receiving direction of the acousticsource 41. The acoustic source 41 lies within the driving path if theacoustic source 41 is localized such that a collision event between thevehicle 10 and the acoustic source 41 would occur if the acoustic source41 does not move away and the vehicle 10 continues following thepre-programmed driving maneuver without control intervention. In such anevent, i.e. when it was estimated that the acoustic source 41 is withinor intersects the driving path of the vehicle 10 and therefore theprocessor 44 estimates that the acoustic source 41 lies within thedriving path of the vehicle 10, the processor 44 further determines arange between the vehicle 10 and the acoustic source 41 in order toconfirm that the acoustic source 41 certainly lies within the drivingpath of the vehicle 10. It is preferred that the processor 44 determinesthe range between the vehicle 10 and the acoustic source 41 only if itis determined that the acoustic source 41 lies within the driving pathof the vehicle 10. The range determination may thus be used to provide aconfirmation whether the acoustic source 41 really lies within thedriving path of the vehicle 10, wherein the receiving directionsdetermined beforehand may only indicate which acoustic sources 41 arecertainly not within the driving path of the vehicle 10. Therefore, itis possible to consider only those acoustic sources 41 in the rangedetermination which are not excluded to lie within the driving pathafter the localization using the receiving directions.

In an exemplary embodiment, it is possible that the localization whichis based on the determined receiving directions provides an informationabout whether the acoustic source 41 can be excluded to lie within thedriving path of the vehicle 10 or whether the acoustic source 41 cannotbe excluded to lie within the driving path of the vehicle 10. Thismeans, a first estimation is carried out whether there is a chance thatthe acoustic source 41 lies within the driving path. If so, the rangebetween the vehicle 10 and the acoustic source 41 is determined tocertainly determine that the acoustic source 41 lies within the drivingpath or not. If the receiving directions for the acoustic source 41 donot indicate that the acoustic source 41 lies within the driving path,then there is no range determination carried out by the processor 44,i.e. some receiving directions can indicate that the acoustic source 41is for sure not in the maneuver path and these are not furtherconsidered. Therefore, it may be possible that it can only be certainlydetermined if the source is in the driving path after the range has beendetermined.

In an exemplary embodiment, the processor 44 determines the rangebetween the vehicle 10 and the at least one acoustic source 41 based ontriangulation using at least two of the audio sensor arrays 40 a-40 d.In this manner, the range, e.g. the distance between the vehicle 10 andthe acoustic source 41 can be determined at a certain point in time.

In an exemplary embodiment, the processor 44 can also obtain audio dataof a plurality of different acoustic sources 41 in the environment ofthe vehicle 10 and determine a receiving direction for each of theplurality of acoustic sources 41 based on the audio data. In particular,the processor 44 determines the location of each acoustic source 41. Thereceiving directions are thus indicative of respective directions of theplurality of acoustic sources 41 relative to the vehicle 10 whichprovides the locations of each of the acoustic sources 41. The processor44 then determines for each of the acoustic sources 41 whether it lieswithin the driving path of the vehicle 10 based on the pre-programmeddriving maneuver and the determined receiving directions, i.e.locations, of each of the plurality of acoustic sources 41. Theprocessor 44 selects those acoustic sources 41 that are determined tolie within the driving path of the vehicle 10 such that the processor 44can then determine a range between the vehicle 10 and each of theselected acoustic sources 41. In particular, a range or distance betweeneach acoustic source 41 that lies on the upcoming driving path (selectedacoustic sources 41) and the vehicle 10 is determined. The otheracoustic sources 41 that are not selected and thus do not lie within thedriving path of the vehicle 10 are discarded. In other words, theprocessor 44 therefore selects all acoustic peaks in the maneuverdirection, i.e. all acoustic sources 41 that lie within the driving pathof the vehicle 10, and discards all other peaks, i.e. all acousticsources 41 that do not lie within the driving path of the vehicle 10.

In an exemplary embodiment, the processor 44 determines a minimum rangeout of the determined ranges between the selected acoustic sources 41and the vehicle 10. In other words, only the selected acoustic sources41 which were determined to lie within the driving path of the vehicle10 and for which a range has therefore been determined are comparedaccording to their ranges such that a single acoustic source 41 from theplurality of acoustic sources 41, which is most proximal to the vehicle10, is selected.

In an exemplary embodiment, the processor 44, for example the arrayselection module 44 c of the processor 44, selects a single one of theaudio sensor arrays 40 a-40 d, for example array 40 c. The selectiontakes place by determining which of the audio sensor arrays 40 a-40 dreceives a maximum signal-to-noise-ratio from the selected singleacoustic source 41 which has been selected as being most proximal to thevehicle 10. In other words, the audio sensor array 40 c which receivesthe highest acoustic signal and the lowest acoustic noise may beselected. The result is that a selected single audio sensor array 40 cis further used by the processor 44 to beamform towards the selectedacoustic source 41 which is most proximal to the vehicle 10, i.e. toselect an audio channel for an audio signal from an audio sensor, e.g.from a single audio sensor, of the selected audio sensor array 40 c.This may be carried out by the spatial object separation module 44 d ofthe processor 44.

In an exemplary embodiment, a non-transitory computer readable medium 46stores pre-trained audio models besides the pre-programmed drivingmaneuver. The audio models may be descriptive for different acousticscenarios or the characteristics of different types or arrangements ofacoustic sources. The processor 44, in particular the patternrecognition module 44 e, is then able to allocate the selected audiosignal to at least one of the pre-trained audio models stored on thenon-transitory computer readable medium 46. This can be understood as acomparison between the selected audio signal and a pre-trained audiomodel which is carried out to obtain a certain probability based onwhich it can be assumed that the selected audio signal belongs to aspecific pre-trained audio model. In other words, the selected audiosignal is classified. This procedure can be carried out by the type andurgency classifier module 44 f of the pattern recognition module 44 e.Therefore, a predetermined probability threshold can be appliedindicating which probability has to be achieved to indicate that thedriving scenario, in particular the acoustic source 41, has beencorrectly identified. The processor 44 can then determine a type of theat least one acoustic source 41 based on the comparison and theprobability calculation. The processor 44 can then also determine anurgency estimation of a current driving scenario by analyzing thedriving situation involving the vehicle 10 and the surrounding acousticsources 41, based on the comparison and the probability calculation. Apositive urgency estimation may indicate an upcoming collision eventbetween the acoustic source 41 and the vehicle 10. The urgencyestimation may thus be dependent on how urgent an intervention of thevehicle control system is required to avoid a collision event. This canbe determined based on a comparison of the selected audio data and theaudio models which provides an indication of a probability for a certaincurrent driving scenario, in particular of a current situationdescribing the positioning and movement of the vehicle 10 and theacoustic source 41. Based on this probability approach, it can bedetermined how urgent a change of the situation is to be initiated toavoid an upcoming dangerous situation or even a collision between theacoustic source 41 and the vehicle 10. Both the non-transitory computerreadable medium 46 and the type and urgency classifier module 44 f areparts of the pattern recognition module 44 e of processor 44. Theurgency estimation may involve an urgency related processing of theaudio data based on a pitch variation under doppler impact.

In an exemplary embodiment, the above described process is iterativelyrepeated by the processor 44 until a clear, i.e. determinable typeand/or urgency estimation is possible. A determinable urgency estimationis present if a positive urgency estimation or a negative urgencyestimation can be made. A positive urgency estimation may indicate alikely upcoming collision event between the acoustic source 41 and thevehicle 10 and that further verification of this urgency estimation maybe required to provide a control intervention for the vehicle 10. Anegative urgency estimation may indicate that a collision event can beexcluded. The processor 44 will obtain second audio data of the at leastone acoustic source 41 if the result of the urgency estimation isindeterminable or unclear, for example when a classification of the sameselected audio signal or another selected audio signal is necessary tocarry out the urgency decision, i.e. to make a positive or negativeurgency estimation. The decision whether an urgency estimation ispositive, negative or indeterminable can be carried out by the urgencydecision module 44 g. If the result of the urgency estimation isindeterminable, another acoustic sensing of the environment can becarried out to receive further audio signals and to obtain acorresponding second audio signal of another driving scenario based onthe obtained second audio data of the at least one acoustic source 41and the set of audio models.

In an exemplary embodiment, the processor 44 obtains further sensor dataof the at least one acoustic source 41 in the environment of the vehicle10. These further sensor data can be optical data from a camera 47 a orLidar sensor 47 b or data from a radar sensor 47 c. The processor 44 hasa sensor data fusion module 44 h which provides fused data based on afusion of the further sensor data of the at least one acoustic source 41with the selected audio data of the at least one acoustic source 41, inparticular the selected audio signal from the selected audio channel.The data fusion may provide a verification of the correctness of theurgency estimation which is based on the audio data obtained from theaudio sensors, i.e. the audio sensor array arrangement 40. The processor44 thus verifies the urgency estimation of the current driving scenariobased on the fused data. If the urgency estimation is confirmed by thefurther sensor data and the data fusion, then the processor 44 controlsthe vehicle 10 based on the verified urgency estimation of the currentdriving scenario.

In an exemplary embodiment, the vehicle 10 is controlled or maneuveredby the processor 44, in particular by the AV controller of the maneuversystem module 30. The controlling and maneuvering may include a changingof the driving path of the vehicle 10 or a stopping the vehicle 10.Changing the driving path may include driving a left turn or a rightturn, etc.

In an exemplary embodiment, the system 1 provides an improved redundancyfor sensor-based environment detection and can compensate unexpectedevents occurring due to failure of sensors or decision logic,obstructions, blind spots, and human behavior in general. The system 1is adapted for to handle unexpected events indicated by a shout or cryof a person, e.g. a pedestrian, upon maneuvering or parking the vehicle10. However, further applications are possible, such as handlingunexpected events indicated by a horn or a screech in the environment.The system 1 improves the safety in maneuvering AV's, in particular thesafety of the drivers and passengers of the AV's, but also the personsin the environment of the vehicle 10.

In an exemplary embodiment, the system 1 provides for a low latencyclassification including a successive evaluation of putative eventsbased on a sensor array detection of a direction of acoustic sources 41relative to the vehicle 10, a maneuver of the vehicle, a range betweenthe acoustic sources 41 and the vehicle 10 and an urgency estimationbeing indicative of a requirement to change a driving condition of thevehicle 10. The duration of the evaluation can be incremented anditeratively carried out until a predetermined detection confidence isreached. This will be described in further detail with reference toFIGS. 3A and 3B.

In an exemplary embodiment, the system 1 also provides a maneuverdependent spatial scan. Therein, events may be incrementally evaluatedonly in the maneuver direction, i.e. only for the acoustic sources 41which are located in the driving path of the vehicle 10. Afterwards, arange estimation only for acoustic sources located in the maneuverdirection (DoA's in maneuver direction) is carried out. Furthermore, thebeamforming is applied only if the acoustic sources 41 and the range aredetermined to be in maneuver direction.

In an exemplary embodiment, the system 1 also provides an architecturefor detecting a short range event. A distributed microphone architectureis provided as, for example, described with the reference to FIGS. 6 to10. Some events can be filtered by energy differences between the audiosensor arrays 40 a-40 d of the audio sensor arrangement 40, wherein theenergy differences are based on the different intensities of differentacoustic signals 41 a received from the acoustic sources 41. By applyingthis, it is possible exploit the car as a blocking element for theelimination of certain acoustic sources 41 which are therefore notconsidered for the urgency estimation.

FIGS. 3A and 3B show a block diagram of a flow chart of an exemplarymethod for adapting a driving condition of a vehicle 10 upon detectingan event in an environment of the vehicle 10. The method is carried outby processor 44 of the system 1 of FIGS. 1 and 2. In the following Mrepresents the number microphones in one audio sensor array, Nrepresents the number of audio sensor arrays, n represents the audiosensor array index, P represents the number of receiving directions ofacoustic sources (i.e. peaks) in maneuver direction, D represents thenumber of receiving directions of acoustic sources (i.e. peaks) inmaneuver direction after an inter-array energy level differenceelimination, d represents the peak index and SU represents a Boolean fora “sound urgent flag”.

In an exemplary embodiment, at step 200, n is set to “0” and SU is setto “0”. At step 200, the method starts collecting samples of acousticsignals from the environment of the vehicle. N audio sensor arrays areused to obtain these samples of acoustic signals from the environment.Therein, the number of audio channels provided to receive the acousticsignals from the environment are determined multiplying N by M. At thebeginning of the iterative process at step 210 shown in FIG. 2,parameter n is incremented. The receiving directions of the acousticsignals is determined separately for each n^(th) audio sensor array atstep 210. In other words, step 210 applies a DoA (Direction ofArrival)—estimation for the n^(th) audio sensor array. After thereceiving directions have been obtained in step 210 by the n^(th) audiosensor array, a determination is made at step 220, whether the acousticsignals, i.e. the peaks, in the environment are in the maneuverdirection of the vehicle. If not, the audio buffer is cleared at step230 and the process begins again with step 200, wherein n is now set to“1”. If yes, the process continues with step 240, where it is determinedif n is equal to N. If not, i.e. if the DoA estimation has not been madefor each n^(th) audio sensor array, then n is again incremented, and thereceiving directions of the acoustic signals (peaks) are determined forthe next audio sensor array again in step 210. If yes, d is set to “0”in step 250. At step 260, an inter-array energy difference between thedifferent audio sensor arrays is determined which may includedetermining an acoustic intensity or energy level for the different Naudio sensor arrays. At step 260, all acoustic sources which areestimated not to lie within the maneuver direction and therefore are notwithin the driving path of the vehicle, can be eliminated, e.g.discarded, and all other acoustic sources that are estimated to liewithin the driving path of the vehicle are selected for furtherconsideration in step 270. At step 270, a range is estimated ordetermined for all the acoustic sources that are possibly located in themaneuver direction of the vehicle. i.e. that are not confirmed to lieoutside of the driving path of the vehicle. At step 280, afterdetermining the ranges or distances between the vehicle and each of theacoustic sources that lie within the driving path, the ranges for theacoustic sources are sorted according to the proximity to the vehicle.At step 290, the acoustic source that is most proximal to the maneuverof the vehicle is selected and parameter d is incremented, i.e. set to“1”. This is, at step 290, a single acoustic source is selected. Afterstep 290, it is still all the audio channels (N multiplied by M) fromwhich the audio data is obtained. However, at step 300, the audio sensorarray having the highest signal-to-noise ratio is selected, so that onlyone audio sensor array with M audio sensors (microphones) is active forthe further process. The other audio sensor arrays not selected due to alower signal-to-noise ratio relative to the selected one are not used inthe further process. The selected audio sensor array then, at step 310selects an audio channel for an audio signal from one of the audiosensors (microphones). This procedure is also referred to as beamformingtowards the direction of the selected acoustic source most proximal tothe vehicle. The result is that only one acoustic source is consideredin the following urgency estimation at step 320 so that a classificationis applied on a clean signal. In particular, the acoustic source isclassified at step 320 using the acoustic audio data via the selectedaudio channel and a set of audio models pre-stored on a non-transitorycomputer readable medium. A comparison between these data is made and aprobability approach for determining the presence of a certain acousticsource and/or a certain driving scenario is carried out. Based on thisprobability approach, an urgency decision is made in step 330. If theurgency decision is positive, parameter SU is set to “1” in step 340which results in an indication of an urgent scenario (sound urgentflag), and a verification of this indication of an urgent scenario iscarried out based on a data fusion with further sensor data from othersensors at step 350. If the urgency decision is negative, no indicationof an urgent scenario (sound urgent flag) is made and SU remains set at“0”. However, the verification of such an indication is also verified bydata fusion in step 350. The further sensor data are obtained from theselected acoustic source most proximate to the vehicle via sensors of adifferent sensor type, such as optical sensors. The verification in step350 is based on a fusion of the further sensor data of the selectedacoustic source with the audio data of the selected acoustic sourcereceived via the selected (beamformed) audio channel. The verificationmay verify the location of the acoustic source relative to the vehicleand/or the type of the acoustic source. Afterwards, at step 360 anotherprobability approach for the presence of a certain acoustic sourceand/or a certain driving scenario is carried out based on the result ofthe verification by data fusion. If it was confirmed by the data fusionthat an urgent scenario is given, then a control intervention by thesystem, in particular the AV controller will be carried out at step 370.If the verification at step 350 is not conformed in step 360, then it isdetermined in step 380 whether parameter d is equal to parameter D, i.e.whether the urgency of all acoustic sources that lie with in the drivingpath has been checked. In particular, if d is not equal to D at step380, then the next proximate acoustic source will be considered startingagain with step 290. If all acoustic sources that lie within the drivingpath have been checked, and therefore d is equal to D, then it ischecked at step 390 whether SU has been set to “1”, for example due to apositive urgency estimation. In this case, the audio buffer is clearedat step 400 and SU is again set to “0”. If no positive urgencyestimation has been made in step 330 and SU is still set to “0” at step380, then it is directly continued again with step 200 where the methodwill again start from the beginning.

In an exemplary embodiment, the vehicle 10 and/or system 1 of FIGS. 1and 2 may be configured to execute the above-described method of FIGS.3A and 3B.

In an exemplary embodiment, steps 200 to 310 as well as steps 380 to 400of FIGS. 3A and 3B may be summarized as a maneuver dependent spatialaudio scan. Steps 320, 330 and 340 together may be summarized as a lowlatency clear case audio classification. Steps 350, 360 and 370 may besummarized as a robust urgency detection. The described method is basedon a microphone system and algorithm for enabling the detection ofevents, for example with low latency, short range, and urgency.

FIG. 4 is an exemplary driving scenario of the vehicle 10 of FIG. 1,wherein the vehicle 10 includes the system 1 (not shown) as describedwith reference to FIG. 2. This driving scenario may be representativefor a so-called maneuver dependent spatial scan in a lowest latencymode. Four acoustic sources 411, 412, 413 and 414 are located in theenvironment of the vehicle 10. In the example of FIG. 4, the audiosensor arrangement 40 of the vehicle 10 includes four audio sensorarrays. It will be appreciated, however, that the arrangement 40 canhave a different number of audio sensor arrays. At first, the receivingdirections (DoA's) of each of the acoustic sources 411, 412, 413 and 414relative to the vehicle 10 are determined using all audio sensor arraysof the audio sensor arrangement 40. Therefore, for each of the acousticsources 411, 412, 413 and 414 receiving directions may be determinedusing two or more of the audio sensor arrays. In this manner, thelocation of each acoustic source 411, 412, 413 and 414 may be determinedbased on the respective two or more receiving directions of therespective audio sensor arrays. Then, in a next step, it is determinedwhether and which of the acoustic sources 411, 412, 413 and 414 lieswithin the driving path 15 of the vehicle based on a pre-programmeddriving maneuver stored in a memory of the vehicle processor (not shown)and the determined receiving directions of the acoustic sources 411,412, 413 and 414. For the acoustic sources 411 and 412, it is estimatedthat they do not lie within the driving path 15 of the vehicle 10. Forthe acoustic sources 413 and 414, it is estimated that they may liewithin the driving path 15 of the vehicle 10 so that both acousticsources 413 and 414 are selected and further considered. At this point,it is possible that it cannot yet be certainly determined which of theacoustic sources 413 and 414 really lies within the driving path 15. Tocertainly determine which of these acoustic sources 413 and 414 lieswithin the driving path 15, a range determination may be necessary. Therange between the vehicle 10 and each of the selected acoustic sources413 and 414 is determined by all audio sensor arrays of the audio sensorarrangement 40. In this way, it is determined that only acoustic source414 lies within the driving path of the vehicle 10. The two arraysreceiving a maximum signal-to-noise ratio are selected to carry out arange calculation between the vehicle 10 and each of the selectedacoustic sources 413 and 414. Then, a beamforming, i.e. a selection of asingle audio channel for the audio signal received from the acousticsource 414 is carried out. Afterwards, an urgency estimation, e.g. anurgency classification, is carried out by using the acoustic audio datavia the selected audio channel and a set of audio models pre-stored inthe memory. If the urgency estimation provides a positive resultindicating that an urgent intervention is required, for example if it isdetected that a collision between the acoustic source 414 and thevehicle will most likely occur if no intervention of the vehiclescontrol system is provided, then the AV controller 34 of the vehicle 10will control the vehicle 10 to avoid such a collision by stopping thevehicle 10 or by changing the maneuver direction.

FIG. 5 is another exemplary driving scenario of the vehicle 10 of FIG.1, wherein the vehicle 10 includes the system 1 (not shown) as describedwith reference to FIG. 2. This driving scenario may be representativefor a so-called maneuver dependent alerting other sources mode. Fouracoustic sources 411, 412, 413 and 414 are located in the environment ofthe vehicle 10. In the example of FIG. 5, the audio sensor arrangement40 of the vehicle 10 includes four audio sensor arrays. It will beappreciated, however, that the arrangement 40 can have a differentnumber of audio sensor arrays. At first, the receiving directions(DoA's) of each of the acoustic sources 411, 412, 413 and 414 relativeto each audio sensor array of the vehicle 10 are determined using allaudio sensor arrays of the audio sensor arrangement 40. Acoustic sources411 and 412 are estimated not to lie within the driving path 15 of thevehicle 10, however, a beamforming, i.e. a selection of a single audiochannel for each of the audio signals received by the acoustic source411 and by the acoustic source 412 is nevertheless carried out.Afterwards, an urgency estimation, e.g. an urgency classification, iscarried out by using the acoustic audio data via the selected audiochannel for each acoustic source 411 and 412 and a set of audio modelspre-stored in the memory. For acoustic source 411, an urgent scenario isdetermined and a low-alert message is sent to the AV controller 34. Foracoustic source 412, the urgency estimation was negative and no alertmessage is sent to the AV controller 34. For both acoustic source 413and acoustic source 414, it is estimated that these lie within thedriving path of the vehicle 10 using all audio sensor arrays of theaudio sensor arrangement. Afterwards, those arrays receiving a maximumsignal-to-noise ratio are selected for each of the acoustic sources 413and 414. Then, the range calculation between the vehicle 10 and each ofthe selected acoustic sources 413 and 414 is carried out. For acousticsource 313, it is then determined that it does not lie within thedriving path 15 of the vehicle 10. In contrast, for acoustic source 414,it is determined that it lies within the driving path 15 of the vehicle10, i.e. the acoustic source 414 is determined to be located in thevehicle maneuver. Then, a beamforming, i.e. a selection of a respectivesingle audio channel for the audio signal received by the acousticsource 414 and for the audio signal received by the acoustic source 413is carried out. Afterwards, for each of the acoustic sources 413 and414, an urgency estimation, e.g. an urgency classification, is carriedout by using the acoustic audio data via the respective selected audiochannels and a respective set of audio models pre-stored in the memory.For the acoustic source 413, this urgency estimation is negative and alow-alert message is sent to the AV controller 34. For acoustic source414, in contrast, the urgency estimation provides a positive resultindicating that an urgent intervention is required. In this case, acritical message is sent to the AV controller 34 of the vehicle 10 whichwill control the vehicle 10 to avoid a collision with acoustic source414 by stopping the vehicle 10 or by changing the maneuver direction.

FIG. 6 is an audio sensor arrangement 40 having a single audio sensorarray 40 a.

FIG. 7 is an audio sensor arrangement 40 of the vehicle 10 of FIG. 1having two rear audio sensor arrays 40 a and 40 b. Such an arrangementprovides a good direction and range determination in rearwarddirections.

FIG. 8 is an audio sensor arrangement 40 of the vehicle 10 of FIG. 1having two centrally arranged audio sensor arrays 40 a and 40 b. Such anarrangement provides a reasonable direction and range determination inforward and rearward directions.

FIG. 9 is an audio sensor arrangement 40 of the vehicle 10 of FIG. 1having two front audio sensor arrays 40 a and 40 b. Such an arrangementprovides a good direction and determination in forward directions.

FIG. 10 is an audio sensor arrangement 40 of the vehicle 10 of FIG. 1having four audio sensor arrays 40 a-40 d. Such an arrangement providesa good direction and determination in all directions.

While at least one exemplary embodiment has been presented in theforegoing detailed description, it should be appreciated that a vastnumber of variations exist. It should also be appreciated that theexemplary embodiment or exemplary embodiments are only examples, and arenot intended to limit the scope, applicability, or configuration of thedisclosure in any way. Rather, the foregoing detailed description willprovide those skilled in the art with a convenient road map forimplementing the exemplary embodiment or exemplary embodiments. Itshould be understood that various changes can be made in the functionand arrangement of elements without departing from the scope of thedisclosure as set forth in the appended claims and the legal equivalentsthereof.

What is claimed is:
 1. A system for adapting a driving condition of avehicle upon detecting an event in an environment of the vehicle,comprising: a non-transitory computer readable medium having storedthereon a pre-programmed driving maneuver of the vehicle, wherein thepre-programmed driving maneuver is indicative of a driving path of thevehicle; a processor configured to obtain audio data of at least oneacoustic source in the environment of the vehicle, to determine areceiving direction of the at least one acoustic source based on theaudio data, the receiving direction being indicative of a direction ofthe at least one acoustic source relative to the vehicle; to determinewhether the at least one acoustic source lies within the driving path ofthe vehicle based on the pre-programmed driving maneuver and thedetermined receiving direction of the at least one acoustic source, andto determine a range between the vehicle and the at least one acousticsource if it is determined that the at least one acoustic source lieswithin the driving path of the vehicle; to control the vehicle based onthe determined range.
 2. The system of claim 1, wherein the processor isfurther configured to determine the range between the vehicle and the atleast one acoustic source only if it is determined that the at least oneacoustic source lies within the driving path of the vehicle.
 3. Thesystem of claim 1, wherein the non-transitory computer readable mediumfurther stores a set of audio models, each of the audio models beingindicative of a respective acoustic scenario; wherein the processor isfurther configured to determine a type of the at least one acousticsource based on the obtained audio data of the at least one acousticsource and the set of audio models.
 4. The system of claim 1, whereinthe non-transitory computer readable medium further stores a set ofaudio models, each of the audio models being indicative of a respectiveacoustic scenario; wherein the processor is further configured todetermine an urgency estimation of a current driving scenario based onthe obtained audio data of the at least one acoustic source and the setof audio models, wherein a positive urgency estimation is indicative ofan upcoming collision event of the at least one acoustic source and thevehicle.
 5. The system of claim 4, wherein the processor is furtherconfigured to obtain second audio data of the at least one acousticsource if the result of the urgency estimation is indeterminable, and tosubsequently determine a second urgency estimation of another drivingscenario based on the obtained second audio data of the at least oneacoustic source and the set of audio models.
 6. The system of claim 4,wherein the processor is further configured to obtain further sensordata of the at least one acoustic source in the environment of thevehicle, and to provide fused data based on a fusion of the furthersensor data of the at least one acoustic source with the audio data ofthe at least one acoustic source.
 7. The system of claim 6, wherein thefurther sensor data is obtained from at least one of a camera, a Lidarand a radar.
 8. The system of claim 6, wherein the processor is furtherconfigured to verify the urgency estimation of the current drivingscenario based on the fused data.
 9. The system of claim 8, wherein theprocessor is further configured to control the vehicle based on theverified urgency estimation of the current driving scenario, whereincontrolling the vehicle by the processor includes one of changing thedriving path of the vehicle and stopping the vehicle.
 10. The system ofclaim 1, further comprising: wherein the acoustic source is at least oneof a person, an animal and a loudspeaker.
 11. The system of claim 1,further comprising: an audio sensor arrangement having a plurality ofaudio sensor arrays, wherein each of the plurality of audio sensorarrays in the audio sensor arrangement is located at a distinct locationof the vehicle.
 12. The system of claim 11, wherein the audio sensorarrangement comprises at least two audio sensor arrays, each of the atleast two audio sensor arrays having at least two audio sensors.
 13. Thesystem of claim 12, wherein the processor is further configured todetermine the range between the vehicle and the at least one acousticsource based on triangulation using the at least two audio sensorarrays.
 14. The system of claim 1, wherein the processor is furtherconfigured to obtain audio data of a plurality of acoustic sources inthe environment of the vehicle, to determine a receiving direction foreach of the plurality of acoustic sources based on the audio data, thereceiving directions being indicative of respective directions of theplurality of acoustic sources relative to the vehicle, and to determinefor each of the plurality of acoustic sources whether it lies within thedriving path of the vehicle based on the pre-programmed driving maneuverand the determined receiving directions of each of the plurality ofacoustic sources.
 15. The system of claim 14, wherein the processor isfurther configured to select the acoustic sources that are determined tolie within the driving path of the vehicle, and to determine a rangebetween the vehicle and each of the selected acoustic sources, and todiscard the acoustic sources that are determined not to lie within thedriving path of the vehicle.
 16. The system of claim 15, wherein theprocessor is further configured to determine a minimum range out of thedetermined ranges between the selected acoustic sources and the vehicle,and to select a single acoustic source from the plurality of acousticsources, which is most proximal to the vehicle.
 17. The system of claim16, further comprising: an audio sensor arrangement having a pluralityof audio sensor arrays, wherein the processor is further configured toselect one audio sensor array receiving a maximum signal-to-noise-ratiofrom the selected single acoustic source being most proximal to thevehicle, and to select an audio channel for an audio signal from anaudio sensor of the selected audio sensor array.
 18. The system of claim17, wherein the processor is further configured to determine an urgencyestimation of a current driving scenario based on the audio signal ofthe selected audio channel and a set of audio models stored on thenon-transitory computer readable medium.
 19. A vehicle for adapting adriving condition upon detecting an event in an environment of thevehicle, comprising: a non-transitory computer readable medium havingstored thereon a pre-programmed driving maneuver of the vehicle, whereinthe pre-programmed driving maneuver is indicative of a driving path ofthe vehicle; a processor configured to obtain audio data of at least oneacoustic source in the environment of the vehicle, to determine areceiving direction of the at least one acoustic source based on theaudio data, the receiving direction being indicative of a direction ofthe at least one acoustic source relative to the vehicle; to determinewhether the at least one acoustic source lies within the driving path ofthe vehicle based on the pre-programmed driving maneuver and thedetermined receiving direction of the at least one acoustic source, andto determine a range between the vehicle and the at least one acousticsource if it is determined that the at least one acoustic source lieswithin the driving path of the vehicle; to control the vehicle based onthe determined range.
 20. A method for adapting a driving condition of avehicle upon detecting an event in an environment of the vehicle,comprising: storing, on a non-transitory computer readable medium, apre-programmed driving maneuver of the vehicle, wherein thepre-programmed driving maneuver is indicative of a driving path of thevehicle; obtaining, by a processor, audio data of at least one acousticsource in the environment of the vehicle, determining, by the processor,a receiving direction of the at least one acoustic source based on theaudio data, the receiving direction being indicative of a direction ofthe at least one acoustic source relative to the vehicle; determining,by the processor, whether the at least one acoustic source lies withinthe driving path of the vehicle based on the pre-programmed drivingmaneuver and the determined receiving direction of the at least oneacoustic source, and determining, by the processor, a range between thevehicle and the at least one acoustic source if it is determined thatthe at least one acoustic source lies within the driving path of thevehicle; controlling the vehicle, by the processor, based on thedetermined range.